An efficient algorithm for mining closed inter-transaction itemsets

Authors:
Anthony J. T. Lee;Chun-Sheng Wang;Wan-Yu Weng;Yi-An Chen;Huei-Wen Wu
Affiliations:
Department of Information Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC;Department of Information Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC;Department of Information Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC;Department of Information Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC;Department of Information Management, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, ROC
Venue:
Data & Knowledge Engineering
Year:
2008

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Abstract

In this paper, we propose an efficient algorithm, called ICMiner (Inter-transaction Closed patterns Miner), for mining closed inter-transaction itemsets. Our proposed algorithm consists of two phases. First, we scan the database once to find the frequent items. For each frequent item found, the ICMiner converts the original transaction database into a set of domain attributes, called a dataset. Then, it enumerates closed inter-transaction itemsets using an itemset-dataset tree, called an ID-tree. By using the ID-tree and datasets to mine closed inter-transaction itemsets, the ICMiner can embed effective pruning strategies to avoid costly candidate generation and repeated support counting. The experiment results show that the proposed algorithm outperforms the EH-Apriori, FITI, ClosedPROWL, and ITP-Miner algorithms in most cases.